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Braze is seeking an Engagement Manager for AI Deployment to lead the execution of AI decisioning solutions for enterprise customers. This is a senior individual contributor role on a growing AI Deployment team, blending tactical leadership, technical expertise, and proactive client management.
Key Responsibilities:
- Own the complete AI deployment lifecycle from use case design through user acceptance testing (UAT), including defining operating models and managing technical setup
- Lead hands-on technical workshops with customers to align on objectives, specifications, model configuration, and integration architecture
- Serve as the primary point of contact for customers throughout deployment, managing deliverables, identifying risks proactively, and communicating clearly with all stakeholders including senior leadership
- Champion process improvement by continuously refining the standardized AI deployment playbook to ensure consistent, high-quality delivery
- Influence the product roadmap by ensuring it remains customer-centric and responsive to evolving customer and team needs
You will work with customers across diverse industries to deploy Braze's AI Decisioning Studio, combining technical depth with strategic client partnership. The role requires navigating complex technical projects, facilitating alignment between marketing, data engineering, and data science teams, and driving continuous operational excellence.
Braze is a leading customer engagement platform recognized as a Leader in marketing technology. The company emphasizes composable intelligence and AI-powered decisioning to enable 1:1 personalized customer experiences at scale.
Requirements:
- 5-7 years of project management, consulting, or professional services experience
- Bachelor's degree in a technical field (advanced degrees such as MBA or MS preferred)
- Demonstrated experience managing technical projects from conception to completion
- Strong background in professional services with expertise leading workshops with senior-level stakeholders
- Hands-on technical experience allowing contribution to architectural and machine learning design at a conceptual level
- Ability to communicate with marketing, data engineering, and data science teams
- Proactive, resourceful mindset with ability to identify unmet needs and develop solutions
- Exceptional organizational skills and clarity in communication
- Confidence in pushing back on requests that don't align with program goals
